Semi-supervised method for image texture classification of pituitary tumors via CycleGAN and optimized feature extraction

Semi-supervised method for image texture classification of pituitary tumors via CycleGAN and optimized feature extraction

Abstract Background Accurately determining the softness level of pituitary tumors preoperatively by using their image textures can provide a basis for surgical options and prognosis. Existing methods for this problem require manual intervention, which could hinder the efficiency and accuracy conside...

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Bibliographic Details
Main Authors: Hong Zhu, Qianhao Fang, Yihe Huang, Kai Xu
Format: Article
Language:English
Published: BMC 2020-09-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Pituitary tumors
CycleGAN
DenseNet
ResNet
Auto-encoder
CRNN
Online Access:http://link.springer.com/article/10.1186/s12911-020-01230-x

Internet

http://link.springer.com/article/10.1186/s12911-020-01230-x

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